ABSTRACT

The computational grid is a collection and aggregation of parallel, distributed, and heterogeneous resources. Grid Scheduling is the complex issue to manage the heterogeneous resources. The proposed approach considers the evolutionary algorithm of Differential Evolution (DE) technique in a modified manner to solve the multi-objective parameters of makespan and flowtime. The proposed grid scheduling approach completes the jobs within minimal time and also it increases the utilization of resources. The proposed DE based grid scheduling algorithm with modified has been tested under the batch mode and the performance of the proposed MDE based algorithm has been compared with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), and the results outperform the compared one.